Days-since tickers for all the natural disasters

You know those signs in workplaces that keep track of days since injury? Making use of NASA APIs, Neal Agarwal used that concept to keep track of natural disasters. As of this writing, it’s been 9,691,764 since the last Apocalyptic Volcanic Eruption (VEI 8). Pretty good.

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Technopolitics of the U.S. census

Dan Bouk and Danah Boyd wrote an essay on the data infrastructure and politics behind the decennial census:

Like all infrastructures, the U.S. decennial census typically lives in the obscurity afforded by technical complexity. It goes unnoticed outside of the small group of people who take pride in being called “census nerds.” It rumbles on, essentially invisible even to those who are counted. (Every 10 years, scores of people who answered the census forget they have done so and then insist that the count must have been plagued by errors since it had missed them, even though it had not.) Almost no one notices the processes that produce census data—unless something goes terribly wrong. Susan Leigh Star and Karen Ruhleder argue that this is a defining aspect of infrastructure: it “becomes visible upon breakdown.” In this paper, we unspool the stories of some technical disputes that have from time to time made visible the guts of the census infrastructure and consider some techniques that have been employed to maintain the illusion of a simple, certain count.

This process, whether we know what’s going on or not, in turn affects voices and democracy across the country. So it’s kind of important.

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Privacy algorithm could lead to Census undercount of small towns

To increase anonymity in the Census records, the bureau is testing an algorithm that removes real people and inserts imaginary people in various locations. As you can imagine, this carries a set of challenges. Gus Wezerek and David Van Riper for New York Times Opinion ask what effects this could have on small towns. [Thanks, Gus]

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Squirrel census count in Central Park

In 2018, there was a squirrel census count at Central Park in New York. New York Times graphics editor Denise Lu participated in the citizen science project “to collect the kind of data that underlies the work I do every day.” Lu did a short but interesting piece on her experience counting squirrels.

You can download the data via NYC Open Data.

Now I’m wondering if I should apply to be a 2020 Census counter. Um, for people, not squirrels.

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Counting and illustrating Game of Thrones deaths

Shelly Tan, for The Washington Post, has been counting on-screen deaths in Game of Thrones over the past few years. As the season ended, Tan described her process in an entertaining Twitter thread:

I kept thinking about how her process transfers to counting all things. You know, like the decennial Census. The hand-wavy process always seems so straightforward. It’s like, sure, it’ll take a while, but the challenge is just time. But then you get into it, and there’s all these small bumps along the way that make everything more complicated. And then you’re like, great, well, I’ve already come this far. Better keep on counting.

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Challenges ahead for the Census count

The 2020 Census is coming up quick, but there’s still a lot up in the air. There’s no director, the bureau has to adjust to budget cuts, and a new digital system that promises to save money hasn’t been fully tested (because of lower funding). Exciting. Alvin Chang for Vox explains in more detail — with cartoons.

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Making the Count

The 2020 Census approaches, and with budget cuts, resignations, and so much stuff up in the air, there’s cause for concern. How will the accuracy of the count compare to others? The distribution of billions of dollars rides on the estimates. The closer the counts are to reality, the more fairly money distributes to communities.

Let me explain.

Imagine we have some amount of money. It’s straightforward to split that money between two people.

With everyone accounted for, it’s also straightforward to split the money among several people.

You can also imagine an even split among even groups of people. A group of three people would get the same amount of money as another group of three people. Seems fair enough.

The challenge arrives, like with most data, when the uncertainty and fuzziness join the party. We might not know the exact number of people in each group. Maybe someone isn’t present for the group counting meeting. Maybe others don’t want to be part of the count because they don’t trust the process. Maybe there wasn’t enough time to count everyone. There are many reasons why someone isn’t explicitly counted.

The counting process grows more complicated when there’s more money and more people.

We could just exclude the missing people from the count. You snooze you lose. Or, in this case, the group with the lower count receives less money units. But that sucks for the people in that group, because they still have to distribute the money they receive among the in-real-life number of people.

So we estimate the number of people in each group. In each state. In each county. City. Neighborhood.

This brings us back to the 2020 Census. There are many groups and many people. There are many dollars (and other resources) to distribute. The country, states, cities, towns, and communities form policies and make decisions based on estimates. It’s not a direct formula between population and money, but they are tightly related. Accurate estimates make for better-informed decisions.

This is a big deal for smaller groups, where a shift in an estimate can be significant percentage-wise.

So as 2020 approaches, let’s aim for higher accuracy and less uncertainty.

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Counting large crowds

So the inauguration was on Friday, and there’s been some disagreement about how many people showed up to the event. It turns out, as one might expect, counting thousands of people moving in and out of a space without some kind of counting mechanism like turnstiles is tricky. The New York Times provides a bit of background.

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